In signal processing systems, the ability to efficiently and accurately reconstruct encoded or compressed data may generally depend on the compatibility of the encoding process and the decoding process. When the encoding and decoding are provided by different systems, for example, when systems from different vendors are utilized, mismatches may occur and the decoding system may have to correct these mismatches by providing additional hardware and/or software resources. Without these additional resources present in the decoding system, the mismatches that may occur may not be correctable and the reconstruction fidelity may significantly degrade.
In video systems, for example, where various implementations of the discrete cosine transform (DCT) and the inverse discrete cosine transform (IDCT) have been used for compression and decompression in a variety of video coding formats, mismatches tend to reduce image quality and may require significant computational complexity to correct. Since a wide range of vendors and/or implementations exist in video systems, mismatch compensation or mismatch correction may generally become a difficult issue to solve. In this regard, several standardization efforts have been initiated to address this concern.
One of the variations of the DCT/IDCT transform pair is in the form of an integer transform. The integer transform usually has the property of an exact inverse relationship between the DCT and IDCT by providing strict constraints on the integer values to be used in implementations. This approach, however, limits that ability of system designers to utilize architectures of different precision that may provide additional benefits to the overall design. A more traditional way of implementing the DCT/IDCT transform pair in video coding applications is by specifying the transform accuracy requirements statistically and then utilizing sample data streams to test whether the implementation meets certain specified requirements. However, while different implementations may statistically fall within the specified requirements for a chosen set of sample data streams, these implementations may still produce significant mismatch errors when used in coding/decoding systems. Moreover, the chosen set of sample data streams may not provide sufficient coverage of the specified requirements to guarantee mismatch-free implementation.
The same considerations may extend to any implementation of forward/inverse transform pairs that may be utilized to perform coding/decoding operations. When transform pairs are implemented using strict constraints, high fidelity reconstruction may be achieved but design flexibility may be significantly limited. On the other hand, when transform pairs are implemented based on statistical requirements, flexible systems may be constructed but mismatch error control operations may still be needed.
Further limitations and disadvantages of conventional and traditional approaches will become apparent to one of skill in the art, through comparison of such systems with some aspects of the present invention as set forth in the remainder of the present application with reference to the drawings.